Introduction to JupyterLab
- What is JupyterLab?
- How can you access it?
- Interface basics
- Resources
- Q & A
What is JupyterLab?
- Browser-based interactive environment
- Combines functional code, data exploration, and presentation in a
single portable file
- Supports Python, R, Julia, and more
- Ideal for data science, research, and teaching
JupyterLab: power of this, without all the clutter
Old School
Or if you prefer, much of this, less clutter
New School
Vanilla out of the box, looks something like this
JupyterLab Launcher
And you can even go inception and Juptyer like this
IDE
Where can you run Jupyter
Jupyter on Your Hardware
- Requires more setup effort
- Limited by your hardware, but keeps data local
- Example of launching local
Jupyter Cloud-Based Options
- Multiple platforms available:
- Google Colab
- Kaggle Notebooks
- Azure Notebooks
- Binder
- GitHub Codespaces
- JupyterHub (e.g., Titan Computing Hub)
Today we will focus on univeral tips for the common experience
- In the interest of time, lets all work from this jupyter lite
example: https://jupyter.org/try-jupyter/lab/
- jupyter lite is limited since it runs in a browswer sandbox
- requires no installation
- does not retain anything
JupyterLab Interface
- Menu Bar: File, Edit, View, Run options
- Left Sidebar: File browser, running kernels,
extensions
- Main Work Area: Notebooks, terminals, text
editors
Operations, Tips, and Shortcuts 1
- Create a notebook
- Open a notebook
- Create a Markdown cell
- Code Cell
- Run cells
Operations, Tips, and Shortcuts 2
- Markdown cell
- Use Command Mode and keyboard shortcuts
- [esc] -[a],[b],[x],[z],[m],[y]
Where to Go from Here
- Experiment with Jupyter to assess its value to your process -Explore
what your colleagues have already done: - CS
- Soc
- Time
Series
- Learn to install and use Jupyter locally
- Self-study via LinkedIn
Learning